ArticleAMB Express2025
Identification and functional characterization of glycosyltransferase-related biomarkers for tuberculosis diagnosis.
Article in AMB Express, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Different MicroRNAs expression inRNA biology · 2026Review
- Article
- A machine learning-based prediction model for treatment efficacy in smear and/or chest X-ray positive tuberculosis patients.BMC infectious diseases · 2026Article
- Functional analysis of distinct factors linked to the development of latent to active tuberculosis.Frontiers in cellular and infection microbiology · 2026Review
- The Evolving Landscape of Host Biomarkers for Diagnosis and Monitoring of Tuberculosis.Biomedicines · 2025Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Tuberculosis (TB) is an infectious disease that presents a serious risk to public health. Glycosyltransferase-related genes (GTRGs) are instrumental in assessing the risk of latent tuberculosis infection progressing to active TB. This study aims to develop novel, accurate, and effective diagnostic markers to enhance the early diagnosis and precision treatment of TB. We employed Weighted Gene Co-expression Network Analysis (WGCNA) to explore key genes that are notably linked toTB. In addition, we employed single-sample Gene Set Enrichment Analysis (ssGSEA) to examine the differences in immune cell infiltration between normal tissues and those affected by TB. The effectiveness of the potential biomarkers was evaluated through Receiver Operating Characteristic (ROC) curves and their expression patterns. We also conducted single-gene enrichment analysis to explore the biological functions and pathway activities linked to the characteristic genes. Finally, we constructed a competitive endogenous RNA (ceRNA) network to elucidate the potential regulatory mechanisms governing these genes. Through the screening of hub genes and differentially expressed genes from the GTRGs, we identified two potential biomarkers: B4GALT5 and KCNJ2. Evaluation results indicated that these characteristic genes displayed strong diagnostic performance in both the training and validation cohorts. Moreover, single-gene enrichment analysis revealed that these genes were primarily enriched in apoptosis pathways closely associated with TB treatment. Additionally, the construction of the mRNA-miRNA-lncRNA network identified 82 miRNAs and 65 lncRNAs. This study elucidates the roles of GTRGs in TB, identifies biomarkers associated with these groups, and establishes the lncRNA expression profile of characteristic genes. These findings provide a theoretical foundation for the early diagnosis of TB.
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